#Pragmatic or #Clinical: Analyzing TikTok Mental Health Videos

Alice Qian Zhang, Ashlee Milton, Stevie Chancellor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

As mental health content on platforms like TikTok increases steeply, it is important for us to characterize and understand how it is shared. Unfortunately, there are no precise mechanisms for identifying different types of mental health content or for users to indicate content preferences. Expanding on prior work and a qualitative typology we discovered, we present a preliminary exploration of features from 169 hand-labeled videos from a dataset of 19,000+ videos related to clinical and pragmatic mental health content. Our findings provide opportunities for future advancements in moderating mental health content and personalizing users' interactions.

Original languageEnglish (US)
Title of host publicationCSCW 2023 Companion - Conference Companion Publication of the 2023 Computer Supported Cooperative Work and Social Computing
EditorsMorgan Ames, Susan Fussell, Eric Gilbert, Vera Liao, Xiaojuan Ma, Xinru Page, Mark Rouncefield, Vivek Singh, Pamela Wisniewski
PublisherAssociation for Computing Machinery
Pages149-153
Number of pages5
ISBN (Electronic)9798400701290
DOIs
StatePublished - Oct 14 2023
Event26th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2023 - Minneapolis, United States
Duration: Oct 14 2023Oct 18 2023

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Conference

Conference26th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2023
Country/TerritoryUnited States
CityMinneapolis
Period10/14/2310/18/23

Bibliographical note

Publisher Copyright:
© 2023 ACM.

Keywords

  • Data Analysis
  • Mental Health
  • TikTok

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